A major cause of coronary artery disease (CAD) is atherosclerosis, which is the thickening of the intima of the medium-sized arteries and consequent narrowing of the artery due to lipid and fibrous tissue deposition. This narrowing of a coronary artery is called stenosis. In order to determine the presence and extent of obstructive CAD when diagnosis is uncertain and CAD cannot be reasonably excluded by non-invasive testing, coronary angiography (angiographic imaging of coronary arteries) is required.
Angiographic imaging of coronary arteries involves introducing a radio-opaque substance into one or more coronary arteries. An x-ray source is directed toward the heart of the patient. An x-ray recorder, such as x-ray film, or x-ray camera, located behind the heart of the patient, records a two-dimensional image of the coronary arteries from a given perspective. Two-dimensional images from different perspectives are then reconstructed to obtain a three-dimensional image of a region of interest.
Coronary angiography is used for assessing the feasibility and appropriateness of various forms of therapy, such as revascularization by percutaneous or surgical intervention. For this purpose, it is necessary to accurately compute the width of stenosed arteries in the heart. To that end, effective image processing techniques for segmentation of arteries are required.
A known technique for image segmentation involves the use of level set functions for curve evolution. For example, the article T. Chan and L. Vese, “Active Contours without Edges” IEEE Trans. Image Processing, Vol. 10, no. 2, pp 266-277, February. 2001, proposes a model for active contours to detect objects in a given image based on the technique of curve evolution using a level set function. Level set methods work very well when there exist homogeneous regions of reasonably large spatial extent. However, in the case of stenosed regions in angiogram images, there is some mixing of the intensity values corresponding to interior and exterior of the arteries. As a result, most often, the stenosed region is simply not identified using level set methods.
Accordingly, there is a need for a robust technique for processing of angiographic images for segmentation of coronary arteries.